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基于神经网络与遗传算法的悬臂式掘进机智能控制系统
引用本文:刘若涵,赵振民,赵杰.基于神经网络与遗传算法的悬臂式掘进机智能控制系统[J].工业仪表与自动化装置,2014(6):67-69.
作者姓名:刘若涵  赵振民  赵杰
作者单位:黑龙江科技大学 电气与控制工程学院,哈尔滨,150022
基金项目:国家自然科学基金项目(51304075);黑龙江省教育厅面上项目(12541706);黑龙江省研究生创新项目
摘    要:由于煤矿巷道内煤层的分布是不均匀的,并且是时时变化的,这就给高效开采带来了难度。悬臂式掘进机在巷道中作业时,会因为煤层分布的不确定性,导致所受的截割阻力不停地变化,因此,要求掘进机可以根据不同的工况,能够快速地、实时地调整悬臂的摆动速度。该文提出了基于神经网络与遗传算法的复合控制理论的悬臂式掘进机的控制模式。该控制系统能有效地提高生产效率,并且安全可靠。

关 键 词:神经网络  遗传算法  悬臂式掘进机  智能控制

The boom-type roadheader intelligent control system besed on neural network and genetic algorithms
LIU Ruohan,ZHAO Zhenmin,ZHAO Jie.The boom-type roadheader intelligent control system besed on neural network and genetic algorithms[J].Industrial Instrumentation & Automation,2014(6):67-69.
Authors:LIU Ruohan  ZHAO Zhenmin  ZHAO Jie
Affiliation:( Institute of Electrical and Control Engineering, Heilongjiang University of Science and Technology, Harbin 150022 China)
Abstract:Since the distribution of the coal seams is uneven and continual variation, it brings diffi-culty to excavate efficiently.When boom-type roadheader is working in the tunnel, because of the uncer-tainty of the distribution of coal seams, cutting resistance suffered by roadheader is changing constantly. So the roadheader should adjust boom swing speed quickly and in real time according to different condi-tions.This paper presents a composite control mode, that is a control theory of boom-type roadheader based on neural network and genetic algorithms, which can improve production efficiency effectively, and safety and reliability.
Keywords:neural network  genetic algorithms  boom-type roadheader  intelligent control
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